长白落叶松含碳率分析及含碳量异速生长模型

doi:10.13287/j.1001-9332.202205.009

应用生态学报 ›› 2022, Vol. 33 ›› Issue (5): 1166-1174.doi: 10.13287/j.1001-9332.202205.009

长白落叶松含碳率分析及含碳量异速生长模型

张悦, 谢龙飞, 董利虎^*

东北林业大学林学院, 森林生态系统可持续经营教育部重点实验室, 哈尔滨 150040

收稿日期:2021-09-02 接受日期:2021-12-02 出版日期:2022-05-15 发布日期:2022-11-15
通讯作者: * E-mail: donglihu2006@163.com
作者简介:张悦, 女, 1996年生, 硕士研究生。主要从事森林含碳量模型构建研究。E-mail: zhangdalianer@163.com
基金资助:
国家自然科学基金项目(31971649)、中央高校基本科研业务费专项资金项目(2572020DR03)、黑龙江省科学技术项目(GX18B041)和黑龙江头雁创新团队计划项目(森林资源高效培育技术研发团队)资助。

Analysis of carbon concentration and allometric growth model of carbon content for Larix olgensis

ZHANG Yue, XIE Long-fei, DONG Li-hu^*

Ministry of Education Key Laboratory of Sustainable Forest Ecosystem Management, School of Forestry, Northeast Forestry University, Harbin 150040, China

Received:2021-09-02 Accepted:2021-12-02 Online:2022-05-15 Published:2022-11-15

摘要/Abstract

摘要： 森林碳储量约占陆地碳储量的45%,准确评估森林碳储量对于森林的科学经营管理及规划具有重要意义。基于2015—2018年黑龙江省佳木斯市孟家岗、尚志帽儿山、小九林场以及东京、林口林业局的77棵人工长白落叶松的解析木数据,分析5种树木成分(即干材、树皮、树枝、树叶和树根)的含碳量分配及含碳率变化,构建了长白落叶松总量及各分项的一元及二元可加性含碳量模型,模型参数估计采用非线性似乎不相关回归模型方法,并采用“刀切法”对模型进行检验,评价其预测能力。结果表明:各分项加权平均含碳率差异显著,树枝(49.3%)>树皮(48.7%)>树叶(48.5%)>干材(48.2%)>树根(47.1%)。地上含碳量约占总含碳量的80%,地下含碳量约占20%。可加性含碳量模型的调整后确定系数R_a²大于0.89,平均绝对误差(MAE)小于4.1 kg,绝大多数模型的平均绝对误差百分比(MAE%)小于30%。引入树高变量,可以有效地提高大部分含碳量模型的拟合效果和预测能力。其中,总量、地上、干材和树皮含碳量模型拟合效果较好,树枝、树叶、树根和树冠含碳量模型拟合效果相对较差。

关键词: 含碳量, 长白落叶松, 可加性模型, 似乎不相关回归

Abstract: Forest carbon storage accounts for about 45% of terrestrial carbon storage. Accurate assessment of forest carbon storage is of great significance to the scientific management and planning of forests. Based on the data of 77 sampling Larix olgensis trees from Mengjiagang, Shangzhi Maoershan, Xiaojiu Forest Farm and Dongjing, Lin-kou Forestry Bureaus of Jiamusi, Heilongjiang Province from 2015 to 2018, we analyzed the partition of carbon content and variation of carbon concentration for five tree components (i.e., wood, bark, branch, leaf, and root). The mono-element and dual-element additive models of carbon content for each component of L. olgensis were deve-loped. The nonlinear seemly unrelated regression was used to estimate the parameters in the additive models, while the jackknife resampling technique was used to verify and evaluate the developed models. The results showed that the weighted mean carbon concentration of each component differed significantly, branches (49.3%) > bark (48.7%) > foliage (48.5%) > wood (48.2%) > root (47.1%). The aboveground and belowground carbon content accounted for about 80% and 20% of the total carbon content, respectively. The adjusted coefficient of determination (R_a²) of additive models of carbon content was greater than 0.89, the mean absolute error was less than 4.1 kg, and the mean absolute error percentage for most models was less than 30%. Adding tree height in the additive models of carbon content could significantly improve model fitting performance and predicting precision. The additive models of carbon content of total, aboveground, wood and bark were better than that of carbon content of branch, foliage, root and crown.

Key words: carbon content, Larix olgensis, additive model, seemingly unrelated regression

张悦, 谢龙飞, 董利虎. 长白落叶松含碳率分析及含碳量异速生长模型[J]. 应用生态学报, 2022, 33(5): 1166-1174.

ZHANG Yue, XIE Long-fei, DONG Li-hu. Analysis of carbon concentration and allometric growth model of carbon content for Larix olgensis[J]. Chinese Journal of Applied Ecology, 2022, 33(5): 1166-1174.

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长白落叶松含碳率分析及含碳量异速生长模型

Analysis of carbon concentration and allometric growth model of carbon content for Larix olgensis

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